As a digital analytics professional, you’ve probably been tasked with collecting business requirements for measuring a new website/app/feature/etc. This seems like a task that’s easy enough, but all too often people get wrapped around the axle and fail to capture what’s truly important from a business users’ perspective. The result is typically a great deal of wasted time, frustrated business users, and a deep-seated distrust for analytics data. All of these problems can be avoided by following a few simple rules for collecting and validating business requirements.
Rule #1: Set Proper Expectations for What’s Really Worth Measuring
You’ve heard the saying from Albert Einstein…Not everything that can be counted counts, and not everything that counts can be counted. Well, Einstein was ahead of his time when it comes to digital analytics. There is an understandable tendency to measure everything, but this certainly doesn’t help when it comes to sifting through data to determine the effectiveness of your digital efforts. In many cases, less is more. Remember that collecting business requirements creates the foundation for developing KPIs to gauge effectiveness of your digital efforts. And, if you’re reading my colleague Tim Wilson’s blog, you know that the “K” in “KPI” is not for “1,000”!
So, the first rule in gathering effective business requirements is sitting down with your business user counterparts and explaining to them that their new digital asset should be measured on the merits of what it’s designed to accomplish with as few metrics as possible. In plain english, you should ask the question, What is this new thing of yours supposed to do? Once you have the answer to that question, you can start digging into the real meat of what’s needed in terms of measuring its performance. Most business users don’t want to spend hours analyzing and interpreting data, so this rule allows you to set the expectation that you can save them time and headaches by distilling the metrics down into the most salient measures.
In my experience I’ve found that asking your stakeholders to do a little homework prior to meeting will help these conversations go much more smoothly. By prompting them with probing questions about which elements of their digital asset are critical and setting expectations about what digital analytics can do well, you will have a much more productive requirements gathering session.
Rule #2: Break Requirements Down into Manageable Categories
When asked which specific things a business user wants to measure on their shiny new digital asset, the conversation usually goes something like this…
Analyst: What data would you like to collect about your new website/app/feature/etc…?
Business User: I don’t know, what do you have?
Analyst: Well, we can collect anything you want, if you just tell me what it is that you want to know.
Business User: Okay, I want to know everything…
Analyst: So, everything is important?
Business User: Yep.
Business User: WTH?
Asking business users what they want to measure — or what data they need — is truly a difficult question to answer. As an analyst, you have to put yourself in their shoes and lead them into data collection conversation with some guidance. I recommend the approach of breaking your measurement requirements down into categories that can be addressed one at a time. In many cases, there will be different stakeholders who want to know different things about their digital asset and the category approach helps you to generate a comprehensive list of requirements while considering everyone’s feedback. The table below illustrates a handful of requirement categories and corresponding questions that a business user might want to know.
The exact categories and business questions will vary based on the digital asset you’re measuring so be sure to customize the categories to take into consideration when you’re measuring a mobile app, checkout feature, or entire website.
Rule #3: Verify Requirements and Provide Example Reports
My third rule for verifying requirements is often overlooked by analysts because it is both time consuming and labor intensive. But, if you do take the time to do this, you’ll not only ensure that you have the right requirements, but that you may also save yourself a lot of work in the long run.
Once you’ve solicited requirements from all stakeholders, go through the exercise of prioritizing and de-duping your list so that you can identify what’s really important. Once you receive stakeholder approval for your list, you should then take the next step of providing an example of the reports that business users will receive once you’re live with data collection. This helps because while you may have a solid understanding of how the data will be represented, you’re typically working with users who aren’t equipped to visualize the output of your requirements. As such, providing a mock-up of an analytics report that shows the key data points you will collect helps to validate that you’ve got the right information. Use this process to also ask stakeholders if they will be able to make decisions about their digital asset given the reports you’re providing. If the answer is no, then you need to keep working on the requirements.
By taking this extra step, you’re not only ensuring that you understood the business requirements, but also providing the opportunity to refine your metrics to capture critical decision-making data. Not only will you impress your stakeholders with your proactive approach, but you’ll also avoid having to go back and implement tracking on something that they may have overlooked during your discovery process.
In summary, collecting business requirements for digital analytics is no easy task. It takes a process to illicit good information and it takes some analytical foresight to visualize the results. These are skills that take time to master, but once you get them right, you’ll be on your way to providing the most useful and pertinent data to your business colleagues.
If you’d like to learn more about gathering bulletproof business requirements, please send me an email. Or better yet, join me for a half-day workshop on Requirements Gathering the Demystified Way in Atlanta prior to Web Analytics Demystified’s ACCELERATE conference, where I will go into detail about what it takes to gather requirements and teach you all the tips and tricks of the trade.
So it’s that time of year again when commercialism runs rampant, people spend with reckless abandon, and at any moment there could be fisticuffs at your local Wal-Mart. But alas, this is Holiday Season in America, so be joyous about it!
I’ve been watching online spending trends for the past decade and most recently tying to discern what impact mobile and social media plays in all that glitters online. All signs indicate that 2013 is door-busting records with all time highs for online sales, yet depending on which data you believe in, there’s different stories to be told.
Two analytics leaders, IBM and Adobe routinely benchmark holiday shopping. And while their methodologies differ, so too does their data. Here’s a snapshot of some of their published findings thus far:
Show me the Money
IBM’s Digital Analytics Benchmark reports a +18.9% increase from 2012 in Black Friday sales during this year’s holiday season. Average Order Value (AOV) was $135 with on average 3.8 items per order.
Adobe’s Digital Index reported slightly higher profits with a 39% increase from 2012 for a whopping $1.93 Billion in online sales. Adobe reported a similar AOV at $139 and also revealed that the peak shopping time on Black Friday was between 11AM and noon ET, when retailers accrued $150 Million during this single profitable hour.
While both companies reported lift on 2013 online sales during these two days of shopping, each indicates substantial lift in Thanksgiving Day sales, which may have cannibalized some of Friday’s profits. And while Cyber Monday numbers are still being tallied, all signs point to the biggest online shopping day yet, which likely has retailers grinning from ear to ear early on in this short 2013 holiday shopping season.
Both indices show mobile as a significant driver in online sales. Adobe reported that on Thanksgiving and Black Friday, nearly one out of every four sales was made via mobile device. IOS devices and in particular, iPads were the device of choice in both company’s findings. Adobe reported that a total of $417 Million was recognized in just two days (Thanksgiving and Black Friday) via iPad sales by businesses within their index.
This should come as no surprise to those of us following the data, but mobile now represents nearly 40% of all Black Friday traffic. That’s a trend that retailers just cannot ignore. And as a consumer, you probably can’t ignore it either. Tactics reported by IBM indicate that retailers sent 37% more push notifications via alerts and popup messages on installed apps during these two heavy online shopping days.
Where in the World?
The biggest discrepancy between the two online shopping benchmarks comes from the geographic perspective. Keep in mind here, that IBM’s Digital Analytics Benchmark is comprised of data from 800 US Retail websites; and the Adobe Digital Index data represents a wholly different set of US retailers that accrued 3 billion online visits during the Thanksgiving to Cyber Monday shopping spree. (Note that exact comparable data isn’t provided in publicly available information.)
Yet, Adobe’s data reflects the majority of online shopping on Black Friday coming from 1) Vermont, 2) Wyoming, 3) South Dakota, 4) North Dakota, and 5) Alaska. They cite weather and rural locations as rationale for these states topping the list. IBM on the other hand, indicates that on Black Friday 2013, the highest spending states from their benchmark include: 1) New York, California, Texas, Florida, and Georgia. It’s not atypical to see variances in data sets, yet keep in mind when interpreting results for yourself, it’s all about the data collection method. Results will vary based on who is in your benchmark and how you’re slicing the data.
While IBM’s early data cited in an article by All Things Digital made the outlook for social appear dreary,
Adobe weighed in with a contradictory and uplifting perspective on social. IBM did not report on social sales for Black Friday in 2013 apparently because the findings weren’t “interesting”, but their report from 2012 showed that directly attributable revenue from social media (last click) was a dismal .34% of Black Friday sales. By my math that equates to a paltry $3.5 Million total online dollars via social media sales for Black Friday. The AllThingsD reporter managed to eek out of Jay Henderson, IBM’s Strategy Director, that social sales were flat again this year. Moreover, the article quotes Henderson as saying “I don’t think the implication is that social isn’t important, but so far it hasn’t proven effective to driving traffic to the site or directly causing people to convert.” Hmm…
However, this year Adobe is telling a slightly different story. According to their Cyber Monday blog post, social media has referred a whopping $150 million in sales in just five days from Thanksgiving to Cyber Monday. While, it’s not clear if they’re tracking using a last- or first-click perspective, this data indicates that social is pulling its share of the holiday sled this 2013 season. Well, at least social is pulling about 2% of the sled based on a total of $7.4 billion in total online sales from Thanksgiving through Cyber Monday.
Whichever metrics you choose to believe, counting dollars in social media ROI is never an easy task and it usually doesn’t lead to riches. I’m about to publish a white paper on this very topic, so if you’d like to learn more about quantifying the impact of social, email me for more info.
The Bottom Line
This holiday season is shaping up to be the biggest yet for retailers of all sizes. Remember when just a few years ago people were afraid to buy ***anything*** online? Well, it certainly appears that those days are gone. So, as the days before Christmas (or whichever holiday you celebrate) wind down, and the free shipping deals get sweeter, and the door-busters swing closed until next year, take a close look at your data to see what the digital data trends leave for you.
Attributing credit across a multitude of marketing efforts is one of those sticky problems in digital analytics that seems to generate a whole lot of controversy. This is a topic that comes up with nearly all of my clients and is one that both Eric T. Peterson and I have been researching and writing about for some time now. My latest findings on attribution will be published in a whitepaper sponsored by Teradata Aster, titled, Attribution Methods and Models: A Marketer’s Framework, but you can tune in to our webcast on January 16th, to get the high notes.
While some pundits will argue that attribution is not worth the trouble and that all attribution models are flawed, others contend that attribution simply requires a healthy dose of marketing science, which will enable marketer’s to reap benefits tenfold. At the risk of opening up a whole can of Marketing Attribution worms, I’ll offer my Marketer’s Framework for Attribution, which is a pragmatic approach to organizing, analyzing, and optimizing your marketing mix using data. But first, let’s define marketing attribution:
Web Analytics Demystified defines Marketing Attribution as:
The process of quantifying the impact of multiple marketing exposures and touchpoints preceding a desired outcome.
The first question that you need to ask yourself is whether or not you really even need to include attribution in your analytical mix of tools, tricks, and technologies. I offer this as a starting point because attribution isn’t easy and if you don’t really need it, then you can save yourself a whole lot of headaches by short-cutting the process and offering a data-informed validation of why you don’t want to mess with attribution.
The approach I offer is shamelessly ripped-off from Derek Tangren of Adobe, who blogged; Do we really need an advanced attribution marketing model? Derek encourages his readers to answer this question by looking at their existing data to determine what percentage of orders occur on a user’s first visit to your website vs. those that occur on multiple visits. I bastardized Derek’s idea and applied it to help marketers understand how many visits typically precede a conversion event. While Derek offers a way to do this using Adobe Omniture, I’ve created a custom report within Google Analytics that does virtually the same thing. I call it the Attribution Litmus Test.
My version is a quick sanity check for those of you running Google Analytics to determine the number of conversions that occur on the first visit versus those that occur on subsequent visits. To use this, you must have your conversion events tagged as Goals within Google Analytics (which you should be doing anyway!). If you’d like to run the Attribution Litmus Test on your own data within Google Analytics, you can add the Custom Report to your GA account by following this link: http://bit.ly/Attribution_litmus_test. Remember that you must have goals set up in Google Analytics for this report to generate properly.
So now that you’ve determined that Attribution is a worthwhile endeavor to pursue for your organization, let’s dive into the Framework. According to a study conducted by eConsultancy, only 19% of Marketers have a framework for analyzing the customer journey across online and offline touch points. Yet, the reality of consumer behavior today illustrates that multi-channel marketing exposures and multiple digital touch points are commonplace. As such, Marketers need a method for understanding their cross-channel customers in a systematic and reproducible way.
Step 1: Identify Your Data Sources
The first step in utilizing an Attribution Framework is to identify and input your data sources. Because advanced attribution requires understanding marketing effectiveness across all channels, it means that you must acquire data from each channel that potentially impacts the customer path to purchase. Typical digital channels may include: display advertising, search, email, affiliates, social media, and website activity.
Step 2: Sequence Your Time Frame
All attribution models must consider time to understand which marketing exposures occurred first, and also to discern the latent impact of exposure across channels. This requires that organizations sequence their data. While numerous data formats will likely go into the model, we’ve seen the greatest success when attribution data is stored and aggregated within a relational database.
Step 3: Apply Attribution Models
The actual attribution models will determine how you look at your data and make determinations about which marketing channels, campaigns, and touch points are effective in the context of your entire marketing mix. There are five models that are commonly used in the attribution world: First Click, Last Click, Uniform, Weighted, Exponential. To learn more about these models, tune into the webcast where I explain each in more detail.
Step 4: Conduct Statistical Analysis
After the data has been prepped, sequenced, and cleansed; this is typically where Data Scientists conduct general queries, apply business logic, and run what-if analyses against the model. At agencies that specialize in attribution modeling like Razorfish, they have an advanced analytics team comprised of data scientists that attack the data. They’re looking for correlations to identify if users are exposed to marketing assets A>B>C, are they likely to take action D?
Step 5: Optimize Marketing Mix
Of course, the ultimate goal in utilizing an attribution framework is to make decisions that impact your marketing efforts. These decisions can be strategic such as: deciding to invest in a new social media channel; discontinuing use of a non-performing affiliate partner; or reallocating budget to highly successful channels. But an attribution model can also play a major role in making daily life marketing decisions such as: which keywords to bid on during a specific campaign; who should receive an email promotion; or where to place that out of home billboard to attract the most attention.
In conclusion, Marketing Attribution continues to be an Achilles’ heel to many marketers. But, the good news is that approaching attribution with the right toolset and a framework for solving the attribution riddle is definitely the way to go. Throughout my latest research, I talked with companies like Barnes & Noble, LinkedIn, and the Gilt Groupe to learn how they’re using and applying Marketing Attribution models. I’ve also had the good fortune to demo some of the latest attribution tools from industry leading vendors like Teradata Aster and Visual IQ. Through this research, I learned that there is some truly innovative work going on with regard to attribution, but there is no single best way to do it. I’d love to hear how you’re solving for attribution. Please shoot me a note, tune into our webcast, or comment on how you’re re-examining attribution.
Before too much time passes during these dog days of summer, I thought that I’d offer a recap of the eMetrics Marketing Optimization Summit that took place in Chicago recently. First of all, Chicago really digs analytics. Despite a smallish eMetrics crowd of around ~100 or so people, there was lots of energy, young talent and academic interest.
I had the privilege of sharing a few minutes of the opening keynote with Jim Sterne where I made a few announcements about the newly rebranded DAA (Digital Analytics Association). I proudly announced that we transitioned 25% of our Board of Directors by adding new members Eric Feinberg, Peter Fader and Terry Cohen to our diverse assembly of directors. I also took the stage in my new role as President of the DAA and shared my thoughts about the epic journey we’ve collectively embarked on in this industry that we call digital analytics. This is a theme that I reiterated during my closing presentation on The Evolution of Analytics, whereby I concluded, that the future state of evolution is up to each of us to determine.
But speaking of future success, I commend the local DAA Chicago Chapter for the great strides they’ve made in not only organizing our open industry meeting, but also in championing the cause for digital analytics in the windy city. The DAA has much better brand recognition and awareness in Chicago than I thought. But I suppose I shouldn’t be too surprised because after all, according to the DAA Compensation scan, Chicago is the second best place to live if your seeking a job in analytics.
Moving onto more details about the conference, Jim Sterne always encourages attendees to measure the value of eMetrics not just in the content, but also in the hallway conversations and the key tibits that you take back to your desk when all the sessions and lobby bar fun is over. In Chicago, for me the hallway conversations focused on several hot topics in analytics including: tag management, privacy and of course, the perennial analytics issues of people, process and technology.
I also learned (privately) that Amazon is doing some crazy brilliant stuff, but it’s so good that they can’t even talk about it. The senior brass at the really good companies are very protective, but web analysts can still be plied (at least a little) with alcohol at a Web Analytics Wednesday.
And finally, people who do know what we do are struggling to pull together the pieces for making an analytics program work…finding staff, selecting tools, building process. These are perennial issues in digital analytics and why we’ve built our consulting practice here at Web Analytics Demystified to help solve these problems.
But as always at eMetrics, I was invigorated to speak with new entrants to digital analytics and the usual suspects as well. For me, I’ll be taking from this eMetrics something back to my desk and to my clients…and that is a fresh perspective.
Anyone who has been in this game for any length of time should recognize that it’s easy to become steeped in your own myopic view of digital analytics and continue to rehash the same perennial issues with the same examples over and over again. Yet, any good analysis – or method of teaching – needs to evolve to remain relevant. And thus, for me this eMetrics taught me that experience needs to be tempered with the fresh eyes of unbridled passion and enthusiasm. While we may hold the frameworks and fundamentals, it is they who hold the spark. I for one appreciate what the next generation of digital analyst is bringing to this industry and hope to learn as much from them as I can offer.
The Web Analyst’s Code of Ethics is a reality! This Code represents an industry effort to promote ethical data practices and treat consumer data with the respect and attention it deserves.
I’m writing this on the eve before the official launch announcement of the Web Analyst’s Code of Ethics here at the WAA Symposium in Austin Texas. As you can see in the video above, this effort is the culmination of a ton of hard work by a community of contributors.
Yet, the conversation isn’t a new one. My partner Eric has been writing about the fact that We are our own worst enemy since August and our internal conversations about privacy regulation and public opinion of tracking practices have been going on long before that. The issue received mainstream attention from the Wall Street Journal in their What They Knowseries, which took a bias view in our opinion. Anything that starts out with the phrase; “Marketers are spying on Internet users…“ is FUD in my opinion.
So, in September of last year we decided to do something about it. I must say that Eric never fails to amaze me in his ability to make things happen, because not 24 hours after our conversation about launching a Code of Ethics, he had one drafted and in my inbox. We decided that the best avenue for getting this code out to the community was to work in conjunction with the WAA, where I am a member of the board. Thus, I shopped it around to my fellow board members and we all agreed that it was something that our industry needed. The issue was brought before the WAA Standards Committee and a sub-committee was formed to hash out the details. And the Code was offered to the community for public comment. After numerous iterations and literally dozens of comments and contributors, we arrived at the final Code you see here.
It’s important to recognize that this Code is a pledge for individuals and not organizations. We created it as such because we know that not every individual will be able to enforce policy within their company, but every individual can inform and educate their peers. Yet, as we state in the pledge itself, “I recognize that we are far stronger as a community…”. And this effort is about a community showing it’s commitment to ethical data collection and utilization practices.
Momentum for this project has been incredible thus far, but our work is far from over. It’s just beginning. Like any good analyst, I’ve created goals and success metrics for the code of ethics that I’ll be tracking and reporting on over time. The video above is the first effort to share a glimpse of the metrics, but ultimately I’m shooting for the following goals:
1) Gain 1,000 Pledges to the Code of Ethics in 2011
2) Attract mainstream media attention to this community effort within the first 90 days of launch (e.g., recognition by @WhatTheyKnow)
3) Ensure that our collective voice is heard by legislators and policy makers before regulation is forced upon us
Let us know what you think about the Code of Ethics here by leaving comments and joining the conversation. Or simply show your support by pledging to follow the Web Analyst’s Code of Ethics.
This weekend the Wall Street Journal produced a well researched article called The Web’s New Gold Mine: Your Secrets. Apparently, it’s the first in a series of articles about Internet tracking practices. It’s entirely informative and chock full of quotes, anecdotes, video and interesting visuals. I highly recommend giving this article a read if you subscribe to the WSJ, or encourage you to join the discussion on their blog. However, I take serious issue with the bias inherent within this first article. The author, Julia Angwin uses phraseology like “the business of spying on consumers”, and “…details about her, all to be put up for sale for a tenth of a penny”. Clearly, the conclusion drawn by the author and presented to readers is that tracking solutions are spawned from malice. I vehemently disagree.
While, it’s true that some tracking can be used for devious function, the majority of uses are fully anonymous and serve to benefit end users exponentially. The reality is that media fragmentation, facilitated by the Internet, has forced advertisers to compete for our attention. To do this, they’re hocking their wares in a significantly more relevant way. By serving up advertising content that’s based on activity, propensity and preference, they are saving us from the irrelevant fire hose of most advertising. Without being coarse, I find that the fact that some consumers are self-conscious and sensitive to advertising that’s targeted to their browsing activity as trivial. It’s trivial compared to the the benefits that targeting delivers to the rest of us.
I’ve got more to say on this topic, a lot more in fact, but I’ll stop short for now. My closing thought is that, while the author of the Web’s New Goldmine may see the art and science of tracking as a boon for advertisers… I see it as a significant win for consumers. A jackpot perhaps. I hope and expect that my online and offline interactions with brands will get increasingly better and more relevant as my interactions continue. Tracking will enable this to happen. But, that’s just me…I’d love to know what you think.
Okay…I’ve been quiet about the Coremetrics acquisition by IBM for long enough now. While the dust still won’t settle until sometime in Q3’10, when this deal passes FTC scrutiny, I’m compelled to weigh in and offer my $.02 USD mainly because there’s been some good dialog in the blogosphere from people I respect like: Eric, Joe Stanhope, Akin and more recently Brian Clifton.
I’ll take a slightly different approach and use the acquisition to talk about the state of the web analytics marketplace. For starters, let me just say that this acquisition was inevitable. So too will Webtrends be acquired by some player looking to incorporate metrics into their overarching set of technology capabilities. And as I blogged earlier this spring, yet another even bigger fish will eat the existing big fish and we’ll utter oooh’s and ahhh’s as the analytics technology market evolves into a vital organ for all businesses with a heartbeat. While not immune to arrhythmia, this course of events shouldn’t really take anyone by surprise. I’ve been saying this for a while now and even penned “Web Analytics is Destined to Become an Integrated Service” back in May 2009 when I wrote the Forrester US Web Analytics Forecast 2008-2014 (subscription required). I’ve been advocating web analytics as a function within the marketing organization, which seems to be a logical orientation. However, it’s interesting that the consumption of analytical technologies has come from a smattering of different perspectives.
Here’s how the post-acquisition landscape looks:
Adobe’s acquisition of Omniture undoubtedly took many by surprise (myself included – although you’re never allowed to admit surprise as an analyst). The promise Adobe made to investors was that they would incorporate the market leading web analytics technology into the creative life-cycle by enabling measurement at the point of content creation. Perhaps that’s not exactly how they positioned it, but that was my impression and they’re now executing on that promise. Say what you want about acquisitions and the slow moving integration process, but Creative Suite 5 debuted in April just six short months after the deal closed, with measurement hooks from FlashPro and Dreamweaver into both SiteCatalyst and Test & Target. They’ve also accomplished this remarkable feat using a visual interface allowing content editors and non power-users the ability to begin measuring their digital assets. This utilization of analytics places measurement at the operational level, yet by and large it’s still within the marketing group.
The Marketer’s Toolbox…
Enter Unica with their rebranded Marketing Innovation product suite where NetInsight (formerly Sane Solutions) web analytics sits at the core. While both Omniture and Coremetrics made pre-acquisition strides to amass a truly effective online marketing suite, they were merely playing second fiddle to Unica Campaign, Interact and Marketing Platform solutions. Unica is widely acclaimed as a leading Campaign Management tool and sits proudly in the marketing departments across many an enterprise business. They’ve worked web analytics into the DNA of their overall marketing perspective and use it to power the automation and decisioning that many organizations strive for with lust and admiration. Their utilization of analytics really does empower analytics as a lynchpin for integrated marketing.
With speculation still swirling about the how’s and why’s of IBM’s intended use of Coremetrics, it’s tough to ignore Coremetrics’ strength in the retail vertical. While Coremetrics has an impressive client based outside of retail, including publishers and financial institutions among others, they’ve clearly got some good mojo going with their triple-A retail clients. Just thinking of how Big Blue will assimilate the nimble teams of relentless Coremetrics marketers in San Mateo and Texas makes me slightly nervous. Not for any loss of focus by the Coremetrics team on their dedication to client support or from their delivery of leading analytical capabilities that they offer – rather – where will this newly acquired asset live within the IBM estate? The way I see it, two possible scenarios can play out here:
1. First is the scenario that Akin speculates upon whereby IBM is folded into the Websphere group and serves to illuminate the value of customer interactions within website platforms across IBM’s customer base. This would greatly benefit Websphere customers although it would narrowly define a finite application of a technology that is so much bigger than just online commerce.
2. The scenario that Eric envisions (and one that I believe would benefit our industry exponentially) is the one where IBM becomes the “business analytics” juggernaut in the enterprise. If this were to occur, IBM would need to integrate its SPSS and Cognos acquisitions to get really crafty about delivering extremely high value digital insights.
These are two very different outcomes and both speculatory, but I’m rooting for the latter simply because it has the potential to push analytics so much further along. My sources tell me that some long-time IBM’ers feel this way too. One confidant with access to IBM brass even shared with me that internally the acquisition will be deemed a failure by some at IBM if Coremetrics isn’t integrated with SPSS and Cognos. That’s great news, because wholesale failure of business analytics isn’t an option.
So here we have Webtrends as the only standalone web analytics player remaining from the set of truly original US-based technologies. They’re doing a good job of playing the part of Switzerland as they not-so-quietly establish a platform of Open Analytics whereby data flows in -and- out of the interface fueling other operations around the business. While this is not the same as an integrated approach, Webtrends is taking a strong stance on have-it-your-way analytics. Their open APIs and REST URLs make it easy to leverage their data collection and pump data to any application within the enterprise. Thus, they too offer an integrated approach yet do so by maintaining a position that supports rather than delivers the adjacent marketing functions.
The Low End Theory…
Any post about the state of the analytics marketplace would be remiss if Google Analytics wasn’t included in the conversation. I include the Big Googley in the Low End Theory – not because they’re trailing – but because they’re sneaky smart. Just in case you haven’t been watching, since Google acquired Urchin Software, GA has been quietly amassing millions of installations across businesses large and small adding to the democratization of web analytics. I’d argue that they’re not doing this in a concerted enterprise-wide way, but they are probably gaining the most ground across the enterprise by sheer adoption and hands-on utilization. What this means is that pockets of users are deploying Google Analytics for very focused use of the data and the organization is becoming more accustomed to seeing GA data and using it to make key decisions in their day-to-day operations.
Many other analytics programs are delivering similar value to business users, yet in an extremely isolated manner with tools like KissMetrics, Twitalyzer, Visible Measures and Radian6 just to name a few. This is truly the low end theory because the data is rarely seen by anyone outside the marketing group, but it’s driving key activity around specific marketing functions without the larger business really taking note. Think grassroots baby – under the radar – with potential super smartie effectiveness.
Can Marketing Come from the Heart?
By now you should be asking yourself; So where’s this all going? Despite how each of the companies I described above fit into the overall aspect of a company’s business, I think that we can all agree that analytics is about understanding business performance. Here is where Eric’s vision of the Coming Revolution in Web Analytics fits into the story and the quietly powerful behemoth that’s already penetrated the enterprise garden sits in wait down in Cary, North Carolina. Whether it’s SAS, another player, or an amalgamation of services from multiple players – analytics needs to be at the heart of the organization. Here’s where my analogy pays off…because if this is to happen, then data becomes the lifeblood of the enterprise and analytics allows companies to relate to their customers and offer more tuned in and relevant products and services. Marketing should control this blood flow but use it to power the brain and the working limbs of the organization. While this may start to look like Business Intelligence, I believe it’s different because it requires real-time information, automated decisioning and ultimately creativity. These are qualities that I have yet to see from a BI tool. But maybe I’m naive.
Before this diatribe gets any longer, and you dear reader need resuscitation I’ll call it quits. But I’ll offer fair warning that this is just the beginning of my thoughts on the matter and there’s more to follow. I’d also love to hear what you think.
I’ve been pondering this blog post for a couple of weeks now since I took the WAA Certification Exam along with eight others in the inaugural proctored exam at eMetrics in San Jose.
To be totally honest, I probably didn’t need to take this test. For starters, I’m not a traditional web analyst that’s down in the trenches doing the hard work of analysis, reporting and translating the massive amounts of data we’re all so fond of collecting into insights and recommendations. While these web analysts have something to prove to their organizations about the value of their jobs and the expertise they posses – frankly I have nothing to prove.
Additionally, I work for a well established consultancy with a great brand reputation and I’m not planning on looking for a new job anytime soon. Our clients are most likely going to work with us regardless of our certification status. Yet, I wanted to take this test because I do advise my clients on what they should be doing with web analytics from a strategic perspective. I speak frequently about analytics and how to interpret and deliver data in the most effective ways. So my vantage point cannot be void of practical knowledge that dictates what’s possible in a realistic world.
Thus, I took the test in part to illustrate to myself that I not only talk the talk, but am willing to put my practical skills to the test. And yes…I passed, so you’ll be seeing the CWA (Certified Web Analyst) designation show up on my credentials.
Further, many of you voted recently to elect me to the Web Analytics Association Board of Directors; and I thank you for that. I took the WAA Certification Exam, so that I could lead by example and educate others about what I genuinely believe to be a valuable test of digital measurement knowledge. I encouraged all of my fellow board members to take the test as well and several have done so and more are sure to follow.
But because I went through the experience of taking this exam, I am uniquely qualified to share my experiences that stretch way beyond the speculation of any detractors that criticize this exam. Thus, I give you the Good…the Bad…and the Ugly of the WAA Certification Exam.
This exam is a true test of analytical knowledge that requires both business acumen and a deep understanding of applied web analytics. Like all things analytics – it’s not easy. In fact, it’s downright hard. The guidance offered by the WAA regarding a recommended 3 years of practical experience is sound advice. And even then, this exam will require web analysts to dig deep into their skill set to come up with not just acceptable answers, but the best answer. Out of the initial nine exam-takers, seven passed the test, which is good. Yet, the minimum passing grade for the exam is 60% and the mean scores for our inaugural group was 61.7% (maybe I should have saved that for the ugly). The high score among all test takers thus far was 70%. While this may open questions about whether or not this test is too hard, to me it shows that there is plenty of runway for analysts to showcase their superstar skills with high scores. And if it was easy, where everyone could pass, then what validation of knowledge would that really be?
As my fellow WAA Board member Vicky Brock Tweeted: “As an employer I’d hire folk who ace this, as it tests analytical skills not recall”. Vicky also shared thoughts on her experience here. Much like Vicky, I believe this exam is a good test of knowledge that requires prospective certified analysts to know their stuff, which in turn demonstrates that the credential holds distinction.
The format is a familiar multiple choice answer system with four possible answers. Like most diligent test takers, I relied on the process of eliminating the ones that I knew were incorrect and then sorting through the remaining choices. This typically left me with two answer choices that could work, but knowing that one was better than the other, I was largely going on instinct to make the right choice. There is also a word question section that offered business scenarios and data sets leaving you to solve problems within the context of a specific business. These questions were the real gems of the exam and guaranteed to make your head spin. I love these types of questions, but perhaps I’m a glutton for punishment.
The big elephant in the room is the price. Without question, taking this exam is a financial commitment. I shelled out the bucks from my own pocket to do it because I believe in the value of certification. We as an industry are gaining momentum so quickly that analytics and data-driven cultures are all the rage today. The use of data is permeating organizations from the tactical to the strategic and ending up on the boardroom table, and in some cases, in financial analyst reports that end up on Wall Street. Yet, despite these significant gains, we have no designation to acknowledge that our Web Analysts are qualified for the job. This certification exam is that designation that will identify the truly proficient practitioners. In my opinion, this exam is worth every penny and I strongly believe that as more and more professionals acquire the CWA accreditation it will become the gold standard by which job candidates, consultants and trusted advisors are selected. When we reach this critical mass, those who aren’t Certified Web Analysts will be questioned with just cause…So why aren’t you certified?
I’ll be the first to admit that their are still some kinks in the system so it’s not perfect. Yet, nobody is so I’m willing to offer some leniency. For me, just downloading the application to sign up for the test was a chore. I offered feedback, so hopefully a fix is in the works now [there is], but when I registered the editable PDF application only worked if you had Acrobat writer on your machine, which I don’t. So after filling out the entire form, I couldn’t save it. I ended up printing out the pages and then scanning them back in to submit my application. Now, that’s more than I’d expect from your average exam taker, but I was on a mission. Also, be prepared to dig out your resume because the application requires listing all of your previous employers, their addresses, manager names and phone numbers. I was toggling between the application and my LinkedIn profile just to complete the darn thing.
**UPDATE** There is now a web based form that serves as the application, so no more downloading the PDF.
Next, it was very challenging for me to prepare for this exam. I did utilize the documents offered by the WAA including the Knowledge Required for Certification and the practice questions. The practice questions were actually great. They helped me to decide whether I was going to take the test and did closely resemble the actual questions on the test. I just wished there were more of them. The Knowledge Required document also contained a great deal of useful information, but after pouring through the 37 pages of material, I was still left feeling unprepared. The document mirrors the UBC course material, so it is thorough in describing what will be offered in terms of knowledge, but the meat of the work isn’t included in this document. It was all menu and no entree. So essentially, the document tells you what you will be tested on, but doesn’t teach any of the concepts. While they clearly state that: “Taking these four courses is not required to sit for the certification test.” those that do will be much better prepared than I was. I know that these courses are incredibly valuable and students rave about their success, but most professionals like myself don’t have the time to endure them – despite their value.
So, I already ranted about the preparation materials and the costs above, but the Ugly for me was determining if I would actually re-take this test if I failed. The feedback that I received from the WAA did contain results for the four sections that were included in the test (Analytical Business Culture, Case Studies, Marketing Campaigns, and Site Optimization) and my scores for each section. Yet, this was the extent of the feedback on my performance. It was up to me to decipher which questions may have been within each of the four categories and where I needed to focus my efforts to better prepare for a re-test. To the credit of the Association, most standardized tests are scored this way and offer similar amounts of feedback – but most tests of this magnitude also have test preparation courses that teach the skills of taking the test and offer extensive feedback on skills necessary to score well on the exam. Thus, it was ugly for me because I can sincerely admit that I wouldn’t have paid to retake this test because I do not know how I would have prepared for a second exam.
The bright spot in this potentially ugly situation is that the WAA Board is committed to endorsing organizations that choose to develop WAA Certification Exam training programs. Since this test is still very new, these programs have yet to emerge, but the opportunity is out there. I want the WAA Certification Program to succeed for the WAA and for our industry. If the test-takers are better prepared to take the test through the help of a training program, then that’s a win-win. This type of prep course would offer me the confidence I needed to take the test again if I had failed…or for those of you taking the exam for the first time. Stay tuned for more news on this front as it develops.
This post is already getting long in the tooth and I’ve said a lot. The bottom line for me is that this exam is a strong indication of the digital measurement skills that an individual brings to his or her organization. Passing the WAA Certification Exam means that an individual is an expert in the field of web analytics. It’s an accomplishment that anyone in our industry should be proud of, and one that should receive accolades on top of accolades.
But that’s enough of my rant…What do you think?
I look forward to starting a long-term dialog on this topic, so please comment, email me or otherwise shout your opinions from the rooftops.
Baseball fans across the nation were smiling this weekend with opening day games around the league. Those of you who know me, recognize that I’m a raging Red Sox fan, but last night’s 8pm start time against the Yankees was just too late for me to catch the entire game. So, upon checking the scores this morning I got to see this cool new interactive game summary on Redsox.com.
The spark lines show Tweet volume with mouseovers that offer details on each individual tweet. And the highlights are actual video clips that fire off a new window right from the summary page. Way to go MLB.com for delivering a simple, yet innovative mix of professional and consumer generated content.
Oh, yeah…the Sox beat the Yankees 9 – 7 in the opener if you’re wondering.
Being a change agent for web analytics requires taking calculated risks, standing up for what you believe, and working diligently to make our industry stronger. I left my job at Forrester Research in part to become a change agent for web analytics and my bid for a seat on the WAA board of directors is the next big step in my journey. But, this quest I cannot fulfill alone – I need your vote. I’ve never run for elected office before so to illustrate my conviction, I borrow words from John F. Kennedy’s 1960 presidential nomination speech and added a few of my own…
“With a deep sense of duty and high resolve, I accept your nomination.” I’ve stated several times before that there is no industry better than web analytics. Our colleagues within web analytics – the practitioners, the vendors, the leaders and gurus – are by and large friendly, approachable, and always willing to lend a hand. It makes working within analytics gratifying and fun. My hope is to elevate these positive attributes of our industry by aligning under the professional organization that we can call our own.
“The times are too grave, the challenge too urgent, and the stakes too high…”
Despite my positivism, we are facing turbulent times as an industry. We need to strengthen our association at a global scale to ensure that we speak with a common voice in all countries and in all languages to distinguish the Web Analytics Association as the undisputed resource for education, standards, research, and advocacy.
“…if we open a quarrel between the present and the past, we shall be in danger of losing the future.” It has recently come to my attention, despite proof from some members that not everyone receives value from the WAA. If elected to the Web Analytics Association board I will dedicate my term to proving the value of our association to members at every level, from student to vendor to advanced consultant. If we cannot recognize our own value, how then can we expect outsiders to accept our mission with the credibility and respect it deserves?
“I believe the times demand new invention, innovation, imagination, decision.” Those of you who know me recognize that I am not one to dwell on the mistakes of our past. Instead, I look to the future to determine how we can improve our situation and our position within the industry. These are exciting times for web analytics but times that will regale us to obscurity if we fail to demonstrate our vision through genuine contributions. We must think differently about how measurement technologies can be applied to today’s challenges and illustrate how the WAA is defining these efforts by taking a decisive leadership stand.
“This is a platform on which I can run with enthusiasm and conviction.”
It is this industry, its people and our collective challenges that I want to champion as a representative of the Web Analytics Association. I’ve stated my intentions here on the WAA web site, but will reiterate the most important. It’s time to stop making excuses and start delivering value to the members of the WAA. A vote for me will get you a dedicated evangelist who is willing to shoulder the burden of hard work and diligence that’s required to orchestrate change in this industry.
I welcome your thoughts and comments about how to improve our industry and will guarantee an open mind throughout my tenure on the Web Analytics Association board of directors if elected. Thanks for reading, Now Get Out And Vote!!
Last night as I was casually perusing the days digital analytics news — yes, yes I really do that — I came across a headline and article that got my attention. While the article’s title ("Top 5 Metrics You’re Measuring Incorrectly") is the sort I am used to seeing in our Buzzfeed-ified world of pithy “made you click” headlines, it was the article’s author that got my attention.
As a digital analytics professional, you’ve probably been tasked with collecting business requirements for measuring a new website/app/feature/etc. This seems like a task that’s easy enough, but all too often people get wrapped around the axle and fail to capture what’s truly important from a business users’ perspective. The result is typically a great deal of wasted time, frustrated business users, and a deep-seated distrust for analytics data.
I am delighted to announce that our Team Demystified business unit is continuing to expand with the addition of Nancy Koons and Elizabeth “Smalls” Eckels. Our Team Demystified efforts are exceeding all expectation and are allowing Web Analytics Demystified to provide truly world-class services to our Enterprise-class clients at an entirely new scale.
In one of my recent Adobe SiteCatalyst (Analytics) "Top Gun" training classes, a student asked me the following question: When should you use a variable (i.e. eVar or sProp) vs. using SAINT Classifications? This is an interesting question that comes up often, so I thought I would share my thoughts on this and my rules of thumb on the topic.
Next month’s ACCELERATE conference in Atlanta on September 18th will be the fifth — FIFTH!!! — one. I wish I could say I’d attended every one, but, sadly, I missed Boston due to a recent job change at the time. I was there in San Francisco in 2010, I made a day trip to Chicago in 2011, and I personally scheduled fantastic weather for Columbus in 2013.
A Big Question that social and digital media marketers grapple with constantly, whether they realize it or not: Is "awareness" a valid objective for marketing activity?
I’ve gotten into more than a few heated debates that, at their core, center around this question. Some of those debates have been with myself (those are the ones where I most need a skilled moderator!).
As I have mentioned in the past, one of the Adobe SiteCatalyst (Analytics) topics I loathe talking about is Product Merchandising. Product Merchandising is complicated and often leaves people scratching their heads in my "Top Gun" training classes. However, many people have mentioned to me that my previous post on Product Merchandising eVars helped them a lot so I am going to continue sharing information on this topic.
When Eric Peterson asked me to lead Team Demystified a year ago, I couldn’t say no! Having seen how hard all of the Web Analytics Demystified partners work and that they are still not able to keep up with the demand of clients for their services, it made sense for Web Analytics Demystified to find another way to scale their services. Since the Demystified team knows all of the best people in our industry and has tons of great clients, it is not surprising that our new Team Demystified venture has taken off as quickly as it has.
Lately, Adobe has been sneaking in some cool new features into the SiteCatalyst product and doing it without much fanfare. While I am sure these are buried somewhere in release notes, I thought I’d call out two of them that I really like, so you know that they are there.
I was reading a post last week by one of the Big Names in web analytics…and it royally pissed me off. I started to comment and then thought, “Why pick a fight?” We’ve had more than enough of those for our little industry over the past few years. So I let it go.
One of my newest clients is in a highly competitive business in which they sell similar products as other retailers. These days, many online retailers have a hunch that they are being “Amazon-ed,” which they define as visitors finding products on their website and then going to see if they can get it cheaper/faster on Amazon.com. This client was attempting to use time spent on page as a way to tell if/when visitors were leaving their site to go price shopping.
One of the most valuable ways to be sure your recommendations are heard is to forecast the impact of your proposal. Consider what is more likely to be heard: "I think we should do X ..." vs "I think we should do X, and with a 2% increase in conversion, that would drive a $1MM increase in revenue ..."
I am delighted to share the news that our 2014 “Advanced Analytics Education” classes have been posted and are available for registration. We expanded our offering this year and will be offering four concurrent analytics and optimization training sessions from all of the Web Analytics Demystified Partners and Senior Partners on September 16th and 17th at the Cobb Galaria in Atlanta, Georgia.
In working with a client recently, an interesting question arose around cart additions. This client wanted to know the order in which visitors were adding products to the shopping cart. Which products tended to be added first, second third, etc.? They also wanted to know which products were added after a specific product was added to the cart (i.e. if a visitor adds product A, what is the next product they tend to add?). Finally, they wondered which cart add product combinations most often lead to orders.
As an analyst, your value is not just in the data you deliver, but in the insight and recommendations you can provide. But what is an analyst to do when those recommendations seem to fall on deaf ears?
If I could give one piece of advice to an aspiring analyst, it would be this: Stop showing your "math". A tendency towards "TMI deliverables" is common, especially in newer analysts. However, while analysts typically do this in an attempt to demonstrate credibility ("See? I used all the right data and methods!") they do so at the expense of actually being heard.
I'm always amazed (read: dismayed) when I see the results of an analysis presented with a key set of the results delivered as a raw table of numbers. It is impossible to instantly comprehend a data table that has more than 3 or 4 rows and 3 or 4 columns. And, "instant comprehension" should be the goal of any presentation of information — it's the hook that gets your audience's brain wrapped around the material and ready to ponder it more deeply.
This post (the download, really — it’s not much of a post) is about dealing with exports from Facebook Insights. If that's not something you do, skip it. Go back to Facebook and watch some cat videos. If you are in a situation where you get data about your Facebook page by exporting .csv or .xls files from the Facebook Insights web interface, then you probably sometimes think you need a 52" monitor to manage the horizontal scrolling.
Having worked as an industry analyst back in the day I still find myself interested in what the analyst community has to say about web analytics, especially when it comes to vendor evaluation. The evaluations are interesting because of the sheer amount of work that goes into them in an attempt to distill entire companies down into simple infographics, tables, and single paragraph summaries.
Funnels, as a concept, make some sense (although someone once made a good argument that they make no sense, since, when the concept is applied by marketers, the funnel is really more a "very, very leaky funnel," which would be a worthless funnel — real-world funnels get all of a liquid from a wide opening through a smaller spout; but, let’s not quibble).
Those of you who have read my blog posts (and book) over the years, know that I have lots of opinions when it comes to web analytics, web analytics implementations and especially those using Adobe Analytics. Whenever possible, I try to impart lessons I have learned during my web analytics career so you can improve things at your organization.
I am excited to announce that registration for ACCELERATE 2014 on September 18th in Atlanta, Georgia is now open. You can learn more about the event and our unique "Ten Tips in Twenty Minutes" format on our ACCELERATE mini-site, and we plan to have registration open for our Advanced Analytics Education pre-ACCELERATE training sessions in the coming weeks.
I recently had a client pose an interesting question related to their shopping cart. They wanted to know the distribution of money its visitors were bringing with them to each step of the shopping cart funnel.
Over the past year, I've run into situations multiple times where I wanted an Adobe Analytics segment to be available in multiple Adobe Analytics platforms. It turns out…that's not as easy as it sounds. I actually went multiple rounds with Client Care once trying to get it figured out. And, I’ve found "the answer" on more than one occasion, only to later realize that that answer was a bit misguided.
If your web analytics work covers websites or apps that span different countries, there are some important aspects of Adobe SiteCatalyst (Analytics) that you must know. In this post, I will share some of the things I have learned over the years related to currencies and exchange rates in SiteCatalyst.
In the last few years, people have become accustomed to using multiple digital devices simultaneously. While watching the recent winter Olympics, consumers might be on the Olympics website, while also using native mobile or tablet apps. As a result, some of my clients have asked me whether it is possible to link visits and paths across these devices so they can see cross-device paths and other behaviors.
I had the pleasure last week of visiting with one of Web Analytics Demystified’s longest-standing and, at least from a digital analytical perspective, most successful clients. The team has grown tremendously over the years in terms of size and, more importantly, stature within the broader multi-channel business and has become one of the most productive and mature digital analytics groups that I personally am aware of across the industry.
As someone in the web analytics field, you probably hear how lucky you are due to the fact that there are always web analytics jobs available. When the rest of the country is looking for work and you get daily calls from recruiters, it isn’t a bad position to be in! At Web Analytics Demystified, we have more than doubled in the past year and still cannot keep up with the demand, so I am reaching out to you ...
Whether you have a single toe dipped in the waters of social media analytics or are fully submerged and drowning, you’ve almost certainly grappled with "engagement." This post isn’t going to answer the question "Is engagement ROI?" ...
Unless you’ve been living under a rock, you have heard (and perhaps grown tired) of the buzzword "big data." But in attempts to chase the "next shiny thing", companies may focus too much on "big data" rather than the "right data."